Search results for: VX2 tumor model

Authors: Sourita Ghosh, Falguni Pati, Suhanya Duraiswamy

Abstract:

Spheroid, a simple three-dimensional cellular aggregate, allows us to simulate the in-vivo complexity of cellular signaling and interactions in greater detail than traditional 2D cell culture. It can be used as an in-vitro model for drug toxicity testing, tumor modeling and many other such applications specifically for cancer. Our work is focused on the development of an affordable, user-friendly, robust, reproducible, high throughput microfluidic device for water in oil droplet production, which can, in turn, be used for spheroids manufacturing. Here, we have investigated the droplet breakup between two non-Newtonian fluids, viz. silicone oil and decellularized liver matrix, which acts as our extra cellular matrix (ECM) for spheroids formation. We performed some biochemical assays to characterize the liver ECM, as well as rheological studies on our two fluids and observed a critical dependence of capillary number (Ca) on droplet breakup and homogeneous drop formation

Keywords: chip less, droplets, extracellular matrix, liver spheroid

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Authors: K. Sekulová, M. Šimon

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This article focuses on upper-extremity musculoskeletal disorders risk assessment model at workplace. In this model are used risk factors that are responsible for musculoskeletal system damage. Based on statistic calculations the model is able to define what risk of MSD threatens workers who are under risk factors. The model is also able to say how MSD risk would decrease if these risk factors are eliminated.

Keywords: ergonomics, musculoskeletal disorders, occupational diseases, risk factors

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Authors: Anthony Usoro

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In this paper, two classes of bilinear time series model are obtained under certain conditions from the general bilinear autoregressive moving average model. Bilinear Autoregressive (BAR) and Bilinear Moving Average (BMA) Models have been identified. From the general bilinear model, BAR and BMA models have been proved to exist for q = Q = 0, => j = 0, and p = P = 0, => i = 0 respectively. These models are found useful in modelling most of the economic and financial data.

Keywords: autoregressive model, bilinear autoregressive model, bilinear moving average model, moving average model

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Authors: Yasser Mahmoudi, Nader Karimi

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The present work examines analytically the effect internal heat generation on temperature fields in a channel partially-filled with a porous under local thermal non-equilibrium condition. The Darcy-Brinkman model is used to represent the fluid transport through the porous material. Two fundamental models (models A and B) represent the thermal boundary conditions at the interface between the porous medium and the clear region. The governing equations of the problem are manipulated, and for each interface model, exact solutions for the solid and fluid temperature fields are developed. These solutions incorporate the porous material thickness, Biot number, fluid to solid thermal conductivity ratio Darcy number, as the non-dimensional energy terms in fluid and solid as parameters. Results show that considering any of the two models and under zero or negative heat generation (heat sink) and for any Darcy number, an increase in the porous thickness increases the amount of heat flux transferred to the porous region. The obtained results are applicable to the analysis of complex porous media incorporating internal heat generation, such as heat transfer enhancement (THE), tumor ablation in biological tissues and porous radiant burners (PRBs).

Keywords: porous media, local thermal non-equilibrium, forced convection, heat transfer, exact solution, internal heat generation

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Authors: Shank Kulkarni, Alireza Tabarraei

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The fantastic properties of polyurea such as flexibility, durability, and chemical resistance have brought it a wide range of application in various industries. Effective prediction of the response of polyurea under different loading and environmental conditions necessitates the development of an accurate constitutive model. Similar to most polymers, the behavior of polyurea depends on both strain and strain rate. Therefore, the constitutive model should be able to capture both these effects on the response of polyurea. To achieve this objective, in this paper, a nonlinear hyper-viscoelastic constitutive model is developed by the superposition of a hyperelastic and a viscoelastic model. The proposed constitutive model can capture the behavior of polyurea under compressive loading conditions at various strain rates. Four parameter Ogden model and Mooney Rivlin model are used to modeling the hyperelastic behavior of polyurea. The viscoelastic behavior is modeled using both a three-parameter standard linear solid (SLS) model and a K-BKZ model. Comparison of the modeling results with experiments shows that Odgen and SLS model can more accurately predict the behavior of polyurea. The material parameters of the model are found by curve fitting of the proposed model to the uniaxial compression test data. The proposed model can closely reproduce the stress-strain behavior of polyurea for strain rates up to 6500 /s.

Keywords: constitutive modelling, ogden model, polyurea, SLS model, uniaxial compression test

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Authors: Hussein Altartouri

Abstract:

In this paper the kinematic and kinetic models of an omnidirectional holonomic mobile robot is presented. The kinematic and kinetic models form the OmniDrive model. Therefore, a mathematical model for the robot equipped with three- omnidirectional wheels is derived. This model which takes into consideration the kinematics and kinetics of the robot, is developed to state space representation. Relative analysis of the velocities and displacements is used for the kinematics of the robot. Lagrange’s approach is considered in this study for deriving the equation of motion. The drive train and the mechanical assembly only of the Festo Robotino® is considered in this model. Mainly the model is developed for motion control. Furthermore, the model can be used for simulation purposes in different virtual environments not only Robotino® View. Further use of the model is in the mechatronics research fields with the aim of teaching and learning the advanced control theories.

Keywords: mobile robot, omni-direction wheel, mathematical model, holonomic mobile robot

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Authors: T. N. Mac, B. Shahbodaghkhan, N. Khalili

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A new elastic-viscoplastic (EVP) constitutive model is proposed for the analysis of time-dependent behavior of clay. The proposed model is based on the bounding surface plasticity and the concept of viscoplastic consistency framework to establish continuous transition from plasticity to rate dependent viscoplasticity. Unlike the overstress based models, this model will meet the consistency condition in formulating the constitutive equation for EVP model. The procedure of deriving the constitutive relationship is also presented. Simulation results and comparisons with experimental data are then presented to demonstrate the performance of the model.

Keywords: bounding surface, consistency theory, constitutive model, viscosity

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Authors: Shazia Bano

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Nanoconjugates that integrate photo-based therapeutics and diagnostics within a single platform promise great advances in revolutionizing cancer treatments. However, to achieve high therapeutic efficacy, designing functionally efficacious nanocarriers to tightly retain the drug, promoting selective drug localization and release, and the validation of the efficacy of these nanoconjugates is a great challenge. Here we have designed smart multiagent, liposome based targeted photoactivatable multiagent nanoconjugates, doped with a photoactivatable chromophore benzoporphyrin derivative (BPD) labelled with an active targeting ligand cetuximab to target the EGFR receptor (over expressed in various cancer cells) to deliver a combination of therapeutic agents. This study establishes a tunable nanoplatform for the delivery of the photoactivatable multiagent nanoconjugates for tumor-specific accumulation and targeted destruction of cancer cells in complex cancer model to enhance the therapeutic index of the administrated drugs.

Keywords: targeting, photodynamic therapy, photoactivatable, nanoconjugates

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Authors: Mustafa Cam, Nedim Ongun, Ufuk Kutluana

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Introduction: Restless LegsSyndrome (RLS) is a common, under-recognized disorder disrupts sleep and diminishes quality of life (1). The most common conditions highly associated with RLS include renalfailure, iron and folic acid deficiency, peripheral neuropathy, pregnancy, celiacdisease, Crohn’sdiseaseandrarelymalignancy (2).Despite a clear relation between low peripheral iron and increased prevalence and severity of RLS, the prevalence and clinical significance of RLS in iron-deficientanemic populations is unknown (2). We report here a case of RLS due to iron deficiency in the setting of neuroendocrinetumor. Report of Case: A 35 year-old man was referred to our clinic with general weakness, weight loss (10 kg in 2 months)and 2-month history of uncomfortable sensations in his legs with urge to move, partially relieved by movement. The symptoms were presented very day, worsening in the evening; the discomfort forced the patient to getup and walk around at night. RLS was severe, with a score of 22 at the International RLS ratingscale. The patient had no past medical history. The patient underwent a complete set of blood analyses and the following ab normal values were found (normal limitswithinbrackets): hemoglobin 9.9 g/dl (14-18), MCV 70 fL (80-94), ferritin 3,5 ng/mL (13-150). Brain and spinemagnetic resonance imaging was normal. The patient consultated with gastroenterology clinic and gastointestinal systemendoscopy was performed for theetiology of the iron deficiency anemia. After the gastricbiopsy, results allowed us to reach the diagnosis of neuroen docrine tumor and the patient referred to oncology clinic. Discussion: The first important consideration from this case report is that the patient was referred to our clinic because of his severe RLS symptoms dramatically reducing his quality of life. However, our clinical study clearly demonstrated that RLS was not the primary disease. Considering the information available for this patient, we believe that the most likely possibility is that RLS was secondary to iron deficiency, a very well-known and established cause of RLS in theliterature (3,4). Neuroendocrine tumors (NETs) are rare epithelial neoplasms with neuroendocrine differentiation that most commonly originate in the lungs and gastrointestinal tract (5). NETs vary widely in their clinical presentation; symptoms are often nonspecific and can be mistaken for those of other more common conditions (6). 50% of patients with reported disease stage have either regional or distant metastases at diagnosis (7). Accurate and earlier NET diagnosis is the first step in shortening the time to optimal care and improved outcomes for patients (8). The most important message from this case report is that RLS symptoms can sometimes be thesign of a life-threatening condition. Conclusion: Careful and complete collection of clinical and laboratory data should be carried out in RLS patients. Inparticular, if RLS onset coincides with weight loss and iron deficieny anemia, gastricendos copy should be performed. It is known about that malignancy is a rare etiology in RLS patients and to our knowledge; it is the first case with neuro endocrine tumor presenting with RLS.

Keywords: neurology, neuroendocrine tumor, restless legs syndrome, sleep

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Authors: Kingsley Nnaemeka Ogbu, Constantine Mbajiorgu

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Vegetation has a marked effect on runoff and has become an important component in hydrologic model. The watershed Resources Management (WRM) model, a process-based, continuous, distributed parameter simulation model developed for hydrologic and soil erosion studies at the watershed scale lack a crop growth component. As such, this model assumes a constant parameter values for vegetation and hydraulic parameters throughout the duration of hydrologic simulation. Our approach is to develop a crop growth algorithm based on the original plant growth model used in the Environmental Policy Integrated Climate Model (EPIC) model. This paper describes the development of a single crop growth model which has the capability of simulating all crops using unique parameter values for each crop. Simulated crop growth processes will reflect the vegetative seasonality of the natural watershed system. An existing model was employed for evaluating vegetative resistance by hydraulic and vegetative parameters incorporated into the WRM model. The improved WRM model will have the ability to evaluate the seasonal variation of the vegetative roughness coefficient with depth of flow and further enhance the hydrologic model’s capability for accurate hydrologic studies

Keywords: crop yield, roughness coefficient, PAR, WRM model

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Authors: Hossain A., Miah S., Ray P. K.

Abstract:

Introduction: Single channel and tri-channel applicators are used in the traditional treatment of cervical cancer. Total reference air kerma (TRAK) and treatment outcomes in high-dose-rate brachytherapy for cervical cancer using single-channel and tri-channel applicators were the main objectives of this retrospective study. Material and Methods: Patients in the radiotherapy division who received brachytherapy, chemotherapy, and external radiotherapy (EBRT) using single and tri-channel applicators were the subjects of a retrospective cohort study from 2016 to 2020. All brachytherapy parameters, including TRAK, were calculated in accordance with the international protocol. The Kaplan Meier method was used to analyze survival rates using a log-rank test. Results and Discussions: Based on treatment times of 15.34 (10-20) days and 21.35 (6.5-28) days, the TRAK for the tri-channel applicator was 0.52 cGy.m² and for the single-channel applicator was 0.34 cGy.m². Based on TRAK, the rectum, bladder, and tumor had respective Pearson correlations of 0.082, 0.009, and 0.032. The 1-specificity and sensitivity were 0.70 and 0.30, respectively. At that time, AUC was 0.71. The log-rank test showed that tri-channel applicators had a survival rate of 95% and single-channel applicators had a survival rate of 85% (p=0.565). Conclusions: The relationship between TRAK and treatment duration and Pearson correlation for the tumor, rectum, and bladder suggests that TRAK should be taken into account for the proper operation of single channel and tri-channel applicators.

Keywords: single-channel, tri-channel, high dose rate brachytherapy, cervical cancer

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Authors: Navkiran Kaur, Apoorva Mathur, Abhishree Agarwal, Sakshi Gupta, Tuhin Rashmi

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Aim: Breast cancer is the most common cancer in women worldwide, and resistance to the current therapeutics, often concurrently, is an increasing clinical challenge. Glycosylation of proteins is one of the most important post-translational modifications. It is widely known that aberrant glycosylation has been implicated in many different diseases due to changes associated with biological function and protein folding. Alterations in cell surface glycosylation, can promote invasive behavior of tumor cells that ultimately lead to the progression of cancer. In breast cancer, there is an increasing evidence pertaining to the role of glycosylation in tumor formation and metastasis. In the present study, an attempt has been made to study the disease associated sialoglycoproteins in breast cancer by using bioinformatics tools. The sequence will be retrieved from UniProt database. A database in the form of a word document was made by a collection of FASTA sequences of breast cancer gene sequence. Glycosylation was studied using yinOyang tool on ExPASy and Differential genes expression and protein analysis was done in context of breast cancer metastasis. The number of residues predicted O-glc NAc threshold containing 50 aberrant glycosylation sites or more was detected and recorded for individual sequence. We found that the there is a significant change in the expression profiling of glycosylation patterns of various proteins associated with breast cancer. Differential aberrant glycosylated proteins in breast cancer cells with respect to non-neoplastic cells are an important factor for the overall progression and development of cancer.

Keywords: breast cancer, bioinformatics, cancer, metastasis, glycosylation

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Authors: Anna Avramenko, Heikki Haario

Abstract:

This paper reports the development and application of a 2D depth-averaged model. The main goal of this contribution is to apply the depth averaged equations to a wind park model in which the treatment of the geometry, introduced on the mathematical model by the mass and momentum source terms. The depth-averaged model will be used in future to find the optimal position of wind turbines in the wind park. K-E and 2D LES turbulence models were consider in this article. 2D CFD simulations for one hill was done to check the depth-averaged model in practise.

Keywords: depth-averaged equations, numerical modeling, CFD, wind park model

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Authors: Jui-Ching Chou

Abstract:

Numerical simulation is a popular method used to evaluate the effects of soil liquefaction on a structure or the effectiveness of a mitigation plan. Many constitutive models (UBCSAND model, PM4 model, SANISAND model, etc.) were presented to model the liquefaction phenomenon. In general, inputs of a constitutive model need to be calibrated against the soil cyclic resistance before being applied to the numerical simulation model. Then, simulation results can be compared with results from simplified liquefaction potential assessing methods. In this article, inputs of the UBCSAND model, a simple elastic-plastic stress-strain model, are calibrated against several popular generic liquefaction triggering curves of simplified liquefaction potential assessing methods via FLAC program. Calibrated inputs can provide engineers to perform a preliminary evaluation of an existing structure or a new design project.

Keywords: calibration, liquefaction, numerical simulation, UBCSAND Model

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Authors: Parveen Kundu, Nitika Chawla, Ruchi Agarwal, Swaran Kaur

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Background: Mature cystic teratoma is a benign, most common tumor of the ovary occurring mostly in young and middle-aged females. This study consists of 19 cases of mature cystic teratomas which were received in the Department Of Pathology over a period of two years. There were malignant transformations observed in three cases, which makes it very important for pathologists to thoroughly examine the entire specimen of mature cystic teratomas. Material and Methods: Nineteen reported cases of mature cystic teratomas were received in Deptt. Of Pathology, BPS GMC Khanpur Kalan, Sonepat, over a two-year period from November 2020 to October 2022 and reviewed retrospectively. Data regarding age, size, laterality, gross, morphological features, and surgery performed were retrieved from pathological archives. Results: In our study, the most common age of presentation was the 20-40 year age group. The most common presenting complaint was fullness in the abdomen or abdominal distension. Four out of 19 cases studied cases presented with bilateral ovarian cysts. Tumor size ranged from 6 to 20 cm in diameter. In seven cases, cysts were greater than or equal to 10 cm in diameter. Three cases showed malignant transformation. Conclusion: It is very important to thoroughly examine the contralateral ovary to rule out bilateral presentation. A furthermost thorough examination is advised in tumors of size >10 cm and in tumors with solid areas to rule out any malignant transformation.

Keywords: teratoma, ovary, malignant, transformation

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Authors: Kingsley Nnaemeka Ogbu, Constantine Mbajiorgu

Abstract:

Vegetation has a marked effect on runoff and has become an important component in hydrologic model. The watershed Resources Management (WRM) model, a process-based, continuous, distributed parameter simulation model developed for hydrologic and soil erosion studies at the watershed scale lack a crop growth component. As such, this model assumes a constant parameter values for vegetation and hydraulic parameters throughout the duration of hydrologic simulation. Our approach is to develop a crop growth algorithm based on the original plant growth model used in the Environmental Policy Integrated Climate Model (EPIC) model. This paper describes the development of a single crop growth model which has the capability of simulating all crops using unique parameter values for each crop. Simulated crop growth processes will reflect the vegetative seasonality of the natural watershed system. An existing model was employed for evaluating vegetative resistance by hydraulic and vegetative parameters incorporated into the WRM model. The improved WRM model will have the ability to evaluate the seasonal variation of the vegetative roughness coefficient with depth of flow and further enhance the hydrologic model’s capability for accurate hydrologic studies.

Keywords: runoff, roughness coefficient, PAR, WRM model

Procedia PDF Downloads 356

Authors: Masahiro Ohmura, Koh Kakusho, Takeshi Okadome

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This paper presents a regression model with autocorrelated errors in which the inputs are social moods obtained by analyzing the adjectives in Twitter posts using a document topic model. The regression model predicts Dow Jones Industrial Average (DJIA) more precisely than autoregressive moving-average models.

Keywords: stock market prediction, social moods, regression model, DJIA

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Authors: Lalita Subedi, Jae Kyoung Chae, Yong Un Park, Cho Kyo Hee, Lee Jae Hyuk, Kang Min Cheol, Sun Yeou Kim

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Neuroinflammation may mediate the relationship between low levels of estrogens and neurodegenerative disease. Estrogens are neuroprotective and anti-inflammatory in neurodegenerative disease models. Due to the long term side effects of estrogens, researches have been focused on finding an effective phytoestrogens for biological activities. Daidzein present in soybeans and its active metabolite equol (7-hydroxy-3-(4'-hydroxyphenyl)-chroman) bears strong antioxidant and anticancer showed more potent anti-inflammatory and neuroprotective role in neuroinflammatory model confirmed its in vitro activity with molecular mechanism through NF-κB pathway. Three major CNS cells Microglia (BV-2), Astrocyte (C6), Neuron (N2a) were used to find the effect of equol in inducible nitric oxide synthase (iNOS), cyclooxygenase (COX-2), MAPKs signaling proteins, apoptosis related proteins by western blot analysis. Nitric oxide (NO) and prostaglandin E2 (PGE2) was measured by the Gries method and ELISA, respectively. Cytokines like tumor necrosis factor-α (TNF-α) and IL-6 were also measured in the conditioned medium of LPS activated cells with or without equol. Equol inhibited the NO production, PGE-2 production and expression of COX-2 and iNOS in LPS-stimulated microglial cells at a dose dependent without any cellular toxicity. At the same time Equol also showed promising effect in modulation of MAPK’s and nuclear factor kappa B (NF-κB) expression with significant inhibition of the production of proinflammatory cytokine like interleukin -6 (IL-6), and tumor necrosis factor -α (TNF-α). Additionally, it inhibited the LPS activated microglia-induced neuronal cell death by downregulating the apoptotic phenomenon in neuronal cells. Furthermore, equol increases the production of neurotrophins like NGF and increase the neurite outgrowth as well. In conclusion the natural daidzein metabolite equol are more active than daidzein, which showed a promising effectiveness as an anti-neuroinflammatory and neuroprotective agent via downregulating the LPS stimulated microglial activation and neuronal apoptosis. This work was supported by Brain Korea 21 Plus project and High Value-added Food Technology Development Program 114006-4, Ministry of Agriculture, Food and Rural Affairs.

Keywords: apoptosis, equol, neuroinflammation, phytoestrogen

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Authors: Adji Achmad Rinaldo Fernandes

Abstract:

SEM analysis is a complex multivariate analysis because it involves a number of exogenous and endogenous variables that are interconnected to form a model. The measurement model is divided into two, namely, the reflective model (reflecting) and the formative model (forming). Before carrying out further tests on SEM, there are assumptions that must be met, namely the linearity assumption, to determine the form of the relationship. There are three modeling approaches to path analysis, including parametric, nonparametric and semiparametric approaches. The aim of this research is to develop semiparametric SEM and obtain the best model. The data used in the research is secondary data as the basis for the process of obtaining simulation data. Simulation data was generated with various sample sizes of 100, 300, and 500. In the semiparametric SEM analysis, the form of the relationship studied was determined, namely linear and quadratic and determined one and two knot points with various levels of error variance (EV=0.5; 1; 5). There are three levels of closeness of relationship for the analysis process in the measurement model consisting of low (0.1-0.3), medium (0.4-0.6) and high (0.7-0.9) levels of closeness. The best model lies in the form of the relationship X1Y1 linear, and. In the measurement model, a characteristic of the reflective model is obtained, namely that the higher the closeness of the relationship, the better the model obtained. The originality of this research is the development of semiparametric SEM, which has not been widely studied by researchers.

Keywords: semiparametric SEM, measurement model, structural model, reflective model, formative model

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Authors: Karen Boaz, C. R. Charan

Abstract:

Background: The infiltration of tumour stroma by eosinophils, Tumor-Associated Tissue Eosinophilia (TATE), is known to modulate the progression of Oral Squamous Cell Carcinoma (OSCC). Eosinophils have direct tumoricidal activity by release of cytotoxic proteins and indirectly they enhance permeability into tumor cells enabling penetration of tumoricidal cytokines. Also, eosinophils may promote tumor angiogenesis by production of several angiogenic factors. Identification of eosinophils in the inflammatory stroma has been proven to be an important prognosticator in cancers of mouth, oesophagus, larynx, pharynx, breast, lung, and intestine. Therefore, the study aimed to correlate TATE with clinical and histopathological variables, and blood eosinophil count to assess the role of TATE as a prognosticator in Oral Squamous Cell Carcinoma (OSCC). Methods: Seventy two biopsy-proven cases of OSCC formed the study cohort. Blood eosinophil counts and TNM stage were obtained from the medical records. Tissue sections (5µm thick) were stained with Haematoxylin and Eosin. The eosinophils were quantified at invasive tumour front (ITF) in 10HPF (40x magnification) with an ocular grid. Bryne’s grading of ITF was also performed. A subset of thirty cases was also assessed for association of TATE with recurrence, involvement of lymph nodes and surgical margins. Results: 1) No statistically significant correlation was found between TATE and TNM stage, blood eosinophil counts and most parameters of Bryne’s grading system. 2) Statistically significant relation of intense degree of TATE was associated with the absence of distant metastasis, increased lympho-plasmacytic response and increased survival (diseasefree and overall) of OSCC patients. 3) In the subset of 30 cases, tissue eosinophil counts were higher in cases with lymph node involvement, decreased survival, without margin involvement and in cases that did not recur. Conclusion: While the role of eosinophils in mediating immune responses seems ambiguous as eosinophils support cell-mediated tumour immunity in early stages while inhibiting the same in advanced stages, TATE may be used as a surrogate marker for determination of prognosis in oral squamous cell carcinoma.

Keywords: tumour-associated tissue eosinophilia, oral squamous cell carcinoma, prognosticator, tumoral immunity

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Authors: Eunji Choi, Borang Park, Youngjae Choi, Jinwoo Moon

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In this study, a predictive model for estimating the metabolism (MET) of human body was developed for the optimal control of indoor thermal environment. Human body images for indoor activities and human body joint coordinated values were collected as data sets, which are used in predictive model. A deep learning algorithm was used in an initial model, and its number of hidden layers and hidden neurons were optimized. Lastly, the model prediction performance was analyzed after the model being trained through collected data. In conclusion, the possibility of MET prediction was confirmed, and the direction of the future study was proposed as developing various data and the predictive model.

Keywords: deep learning, indoor quality, metabolism, predictive model

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Authors: Alan Wan

Abstract:

In recent years, the body of literature on frequentist model averaging in statistics has grown significantly. Most of this work focuses on models with different mean structures but leaves out the variance consideration. In this paper, we consider a regression model with multiplicative heteroscedasticity and develop a model averaging method that combines maximum likelihood estimators of unknown parameters in both the mean and variance functions of the model. Our weight choice criterion is based on a minimisation of a plug-in estimator of the model average estimator's squared prediction risk. We prove that the new estimator possesses an asymptotic optimality property. Our investigation of finite-sample performance by simulations demonstrates that the new estimator frequently exhibits very favourable properties compared to some existing heteroscedasticity-robust model average estimators. The model averaging method hedges against the selection of very bad models and serves as a remedy to variance function misspecification, which often discourages practitioners from modeling heteroscedasticity altogether. The proposed model average estimator is applied to the analysis of two real data sets.

Keywords: heteroscedasticity-robust, model averaging, multiplicative heteroscedasticity, plug-in, squared prediction risk

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Authors: Myung Hwan Na, Ho- Chun Song, EunHee Hong

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We widely use normal linear mixed-effects model to analysis data in repeated measurement. In case of detecting heteroscedasticity and the non-normality of the population distribution at the same time, normal linear mixed-effects model can give improper result of analysis. To achieve more robust estimation, we use heavy tailed linear mixed-effects model which gives more exact and reliable analysis conclusion than standard normal linear mixed-effects model.

Keywords: reliability, tires, field data, linear mixed-effects model

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Authors: Abdoullah Fath-Allah, Laila Cheikhi, Rafa E. Al-Qutaish, Ali Idri

Abstract:

The e-government emerging concept transforms the way in which the citizens are dealing with their governments. Thus, the citizens can execute the intended services online anytime and anywhere. This results in great benefits for both the governments (reduces the number of officers) and the citizens (more flexibility and time saving). Therefore, building a maturity model to assess the e-government portals becomes desired to help in the improvement process of such portals. This paper aims at proposing an e-government maturity model based on the measurement of the best practices’ presence. The main benefit of such maturity model is to provide a way to rank an e-government portal based on the used best practices, and also giving a set of recommendations to go to the higher stage in the maturity model.

Keywords: best practices, e-government portal, maturity model, quality model

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Authors: I. C. Tolias, A. G. Venetsanos, N. Markatos

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In the present work, CFD simulations of a large scale open deflagration experiment are performed. Stoichiometric hydrogen-air mixture occupies a 20 m hemisphere. Two combustion models are compared and are evaluated against the experiment. The Eddy Dissipation Model and a Multi-physics combustion model which is based on Yakhot’s equation for the turbulent flame speed. The values of models’ critical parameters are investigated. The effect of the turbulence model is also examined. k-ε model and LES approach were tested.

Keywords: CFD, deflagration, hydrogen, combustion model

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Authors: J. Rhodes, V. Cheng, P. Lok

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The aim of this study is to develop a parsimonious model that explains the effect of different stimulus on a tourist’s intention to visit a new destination. The model consists of destination trust and interest as the mediating variables. The model was tested using two different types of stimulus; both studies empirically supported the proposed model. Furthermore, the first study revealed that advertising has a stronger effect than positive online reviews. The second study found that the peripheral route of the elaboration likelihood model has a stronger influence power than the central route in this context.

Keywords: advertising, electronic word-of-mouth, elaboration likelihood model, intention to visit, trust

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Authors: Ahmad Sarfaraz, Raiyad Herwies

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In this paper, a multi-criteria decision making analysis is used to help any organization selects the best KM tool that fits and serves its needs. The AHP model is used based on a previous study to highlight and identify the main criteria and sub-criteria that are incorporated in the selection process. Different KM tools alternatives with different criteria are compared and weighted accurately to be incorporated in the GP model. The main goal is to combine the GP model with the AHP model to ensure that selecting the KM tool considers the resource constraints. Two important issues are discussed in this paper: how different factors could be taken into consideration in forming the AHP model, and how to incorporate the AHP results into the GP model for better results.

Keywords: knowledge management, analytical hierarchy process, goal programming, multi-criteria decision making

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Authors: Kuplevatsky V., Kuplevatskay, Cherkashin M., Berezina N.

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After 6 months, a violation of the differentiation of the structure of the gland due to edema in 100%. 20% retained signs of a tumor according to DWI/ADC data. By 12 months, the reduction in the size of the gland is 100%. In all cases, no diffusion restriction was observed. The study after 18 months showed no significant changes in all (100%) patients. In the study, 24 months after treatment, the size of the gland was stable in all cases (+/- up to 5%). Diffuse decrease in T2VI signals from peripheral zones, without signs of diffusion restriction in 100%. After 30 months, signs of recovery of adenomatous changes in the transient zone were revealed in 85%. After 36 and 42 months, the restoration of organ differentiation was observed in 93% of patients. In 4 patients, by the 48th month, signs of biochemical relapse were clinically noted. According to the MRI data, signs of a local relapse were revealed. After 48 months, there were signs of restoration of organ differentiation, which allowed the use of PI-RADS criteria. The study after 54 months showed no changes compared to the control. 60 months after treatment, 97% of patients showed a restoration of differentiation of the gland structure, which allows evaluating the organ according to PI-RADS criteria Conclusions: The beginning of restoration of the structure of the prostate gland began 24 months after proton radiation therapy, the PI-RADS criteria can be fully applied after 48 months of treatment. Control studies every 6 months without clinical signs of relapse are not advisable. Local control of the prostate tumor after proton radiation therapy was achieved in 95% of patients during the entire follow-up period ( 60 months).

Keywords: proton therapy, prostate cancer, MRI imaging, PI-RADS

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Authors: Prashantkumar Waghe, N. Prakash, N. D. Prasada, L. V. Lokesh, M. Vijay Kumar, Vinay Tikare

Abstract:

Arsenic is a naturally occurring metalloid with potent toxic effects. It is ubiquitous in the environment and released from both natural and anthropogenic sources. It has the potential to cause various health hazards in exposed populations. Arsenic exposure through drinking water is considered as one of the most serious global environmental threats including Southeast Asia. The aim of present study was to evaluate the modulatory role of subacute exposure to sodium (meta) arsenite on the antinociceptive, anti-inflammatory and antipyretic responses mediated by meloxicam in rats. Rats were exposed to arsenic as sodium arsenite through drinking water for 28 days. A single dose of meloxicam (2 mg/kg b. wt.) was administered by oral gavage on the 29th day. The exact time of meloxicam administration depended on the type of test. Rats were divided randomly into 5 groups (n=6). Group I served as normal control and received arsenic free drinking water, while rats in group II were maintained similar to Group I but received meloxicam on 29th day. Groups III, IV and V were pre-exposed to arsenic through drinking water at 0.5, 5.0 and 50 ppm, respectively, for 28 days and was administered meloxicam next day and; pain and inflammation carried out by using formalin-induced nociception and carrageenan-induced inflammatory model(s), respectively by using standard protocol. For assessment of antipyretic effects, one more additional group (Group VI) was taken and given LPS @ 1.8 mg/kg b. wt. for induction of pyrexia (LPS control). Higher dose of arsenic inhibited the meloxicam mediated antinociceptive, anti-inflammatory and antipyretic responses. Further, meloxicam inhibited the arsenic induced level of tumor necrosis factor-α, inetrleukin-1β, interleukin -6 and COX2 mediated prostaglandin E2 in hind paw muscle. These results suggest a functional antagonism of meloxicam by arsenic. This may relate to arsenic mediated local release of tumor necrosis factor-α, inetrleukin-1β, interleukin -6 releases COX2 mediated prostaglandin E2. Based on the experimental study, it is concluded that sub-acute exposure to arsenic through drinking water aggravate pyrexia, inflammation and pain at environment relevant concentration and decrease the therapeutic efficacy of meloxicam at higher level of arsenite exposure. Thus, the observation made has clinical relevance in situations where animals are exposed to arsenite epidemic geographical locations.

Keywords: arsenic, analgesic activity, meloxicam, Wistar rats

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Authors: Lu Zhao, Nadir Farhi, Yeltsin Valero, Zoi Christoforou, Nadia Haddadou

Abstract:

In this paper, a long short-term memory (LSTM) neural network model is proposed to replicate simultaneously car-following and lane-changing behaviors in road networks. By combining two kinds of LSTM layers and three input designs of the neural network, six variants of the LSTM model have been created. These models were trained and tested on the NGSIM 101 dataset, and the results were evaluated in terms of longitudinal speed and lateral position, respectively. Then, we compared the LSTM model with a classical car-following model (the intelligent driving model (IDM)) in the part of speed decision. In addition, the LSTM model is compared with a model using classical neural networks. After the comparison, the LSTM model demonstrates higher accuracy than the physical model IDM in terms of car-following behavior and displays better performance with regard to both car-following and lane-changing behavior compared to the classical neural network model.

Keywords: traffic modeling, neural networks, LSTM, car-following, lane-change

Procedia PDF Downloads 230